Assessing the role of EO in biodiversity monitoring: options for integrating in-situ observations with EO within the context of the EBONE concept

The European Biodiversity Observation Network (EBONE) is a European contribution on terrestrial monitoring to GEO BON, the Group on Earth Observations Biodiversity Observation Network. EBONE’s aims are to develop a system of biodiversity observation at regional, national and European levels by assessing existing approaches in terms of their validity and applicability starting in Europe, then expanding to regions in Africa. The objective of EBONE is to deliver: 1. A sound scientific basis for the production of statistical estimates of stock and change of key indicators; 2. The development of a system for estimating past changes and forecasting and testing policy options and management strategies for threatened ecosystems and species; 3. A proposal for a cost-effective biodiversity monitoring system. There is a consensus that Earth Observation (EO) has a role to play in monitoring biodiversity. With its capacity to observe detailed spatial patterns and variability across large areas at regular intervals, our instinct suggests that EO could deliver the type of spatial and temporal coverage that is beyond reach with in-situ efforts. Furthermore, when considering the emerging networks of in-situ observations, the prospect of enhancing the quality of the information whilst reducing cost through integration is compelling. This report gives a realistic assessment of the role of EO in biodiversity monitoring and the options for integrating in-situ observations with EO within the context of the EBONE concept (cfr. EBONE-ID1.4). The assessment is mainly based on a set of targeted pilot studies. Building on this assessment, the report then presents a series of recommendations on the best options for using EO in an effective, consistent and sustainable biodiversity monitoring scheme. The issues that we faced were many: 1. Integration can be interpreted in different ways. One possible interpretation is: the combined use of independent data sets to deliver a different but improved data set; another is: the use of one data set to complement another dataset. 2. The targeted improvement will vary with stakeholder group: some will seek for more efficiency, others for more reliable estimates (accuracy and/or precision); others for more detail in space and/or time or more of everything. 3. Integration requires a link between the datasets (EO and in-situ). The strength of the link between reflected electromagnetic radiation and the habitats and their biodiversity observed in-situ is function of many variables, for example: the spatial scale of the observations; timing of the observations; the adopted nomenclature for classification; the complexity of the landscape in terms of composition, spatial structure and the physical environment; the habitat and land cover types under consideration. 4. The type of the EO data available varies (function of e.g. budget, size and location of region, cloudiness, national and/or international investment in airborne campaigns or space technology) which determines its capability to deliver the required output. EO and in-situ could be combined in different ways, depending on the type of integration we wanted to achieve and the targeted improvement. We aimed for an improvement in accuracy (i.e. the reduction in error of our indicator estimate calculated for an environmental zone). Furthermore, EO would also provide the spatial patterns for correlated in-situ data. EBONE in its initial development, focused on three main indicators covering: (i) the extent and change of habitats of European interest in the context of a general habitat assessment; (ii) abundance and distribution of selected species (birds, butterflies and plants); and (iii) fragmentation of natural and semi-natural areas. For habitat extent, we decided that it did not matter how in-situ was integrated with EO as long as we could demonstrate that acceptable accuracies could be achieved and the precision could consistently be improved. The nomenclature used to map habitats in-situ was the General Habitat Classification. We considered the following options where the EO and in-situ play different roles: using in-situ samples to re-calibrate a habitat map independently derived from EO; improving the accuracy of in-situ sampled habitat statistics, by post-stratification with correlated EO data; and using in-situ samples to train the classification of EO data into habitat types where the EO data delivers full coverage or a larger number of samples. For some of the above cases we also considered the impact that the sampling strategy employed to deliver the samples would have on the accuracy and precision achieved. Restricted access to European wide species data prevented work on the indicator ‘abundance and distribution of species’. With respect to the indicator ‘fragmentation’, we investigated ways of delivering EO derived measures of habitat patterns that are meaningful to sampled in-situ observations

Reviews and syntheses: remotely sensed optical time series for monitoring vegetation productivity

Vegetation productivity is a critical indicator of global ecosystem health and is impacted by human activities and climate change. A wide range of optical sensing platforms, from ground-based to airborne and satellite, provide spatially continuous information on terrestrial vegetation status and functioning. As optical Earth observation (EO) data are usually routinely acquired, vegetation can be monitored repeatedly over time, reflecting seasonal vegetation patterns and trends in vegetation productivity metrics. Such metrics include gross primary productivity, net primary productivity, biomass, or yield. To summarize current knowledge, in this paper we systematically reviewed time series (TS) literature for assessing state-of-the-art vegetation productivity monitoring approaches for different ecosystems based on optical remote sensing (RS) data. As the integration of solar-induced fluorescence (SIF) data in vegetation productivity processing chains has emerged as a promising source, we also include this relatively recent sensor modality. We define three methodological categories to derive productivity metrics from remotely sensed TS of vegetation indices or quantitative traits: (i) trend analysis and anomaly detection, (ii) land surface phenology, and (iii) integration and assimilation of TS-derived metrics into statistical and process-based dynamic vegetation models (DVMs). Although the majority of used TS data streams originate from data acquired from satellite platforms, TS data from aircraft and unoccupied aerial vehicles have found their way into productivity monitoring studies. To facilitate processing, we provide a list of common toolboxes for inferring productivity metrics and information from TS data. We further discuss validation strategies of the RS data derived productivity metrics: (1) using in situ measured data, such as yield; (2) sensor networks of distinct sensors, including spectroradiometers, flux towers, or phenological cameras; and (3) inter-comparison of different productivity metrics. Finally, we address current challenges and propose a conceptual framework for productivity metrics derivation, including fully integrated DVMs and radiative transfer models here labelled as “Digital Twin”. This novel framework meets the requirements of multiple ecosystems and enables both an improved understanding of vegetation temporal dynamics in response to climate and environmental drivers and enhances the accuracy of vegetation productivity monitoring

Semi-natural grasslands under impact of changing land use during last 30 years: Trollio-Cirsietum community in the Liptov region (N Slovakia)

Significant transformation of agriculture took place in Central Europe during the second half of the 20th century. The paper reviews the nature and consequences of this process in terms of grassland management and land use changes in the Liptov region (N Slovakia) and their impacts on plant communities of fen meadows ( Caricion davallianae, Caricion fuscae ), wet meadows ( Calthion ) and mesophilous grasslands ( Arrhenatherion, Cynosurion ). We studied in detail the changes in structure of the rare plant community Trollio-Cirsietum (Kühn 1937) Oberd. 1957 that occurred between the first period (1974–1983) and the second period (2002–2003). We recorded the decrease in abundance of species characteristic for permanently wet and fen meadows (alliances Calthion and Caricion davallianae) and the increase in abundance of characteristic species of seasonally dried, mesophilous and thermophilous meadows and mesophilous fringes (classes Molinio-Arrhenatheretea, Festuco-Brometea and alliances Molinion caeruleae, Bromion erecti and Trifolion medii ). In the second studied period, a large group of mesophilous and thermophilous species appeared as new in this wet-meadow community. A cumulative impact of different factors, especially drainage and intensification of surrounding grasslands as well as abandonment of the community can represent reasons responsible for observed changes. Regardless identified changes, the community still maintains its typical character in significant proportion of the studied sites and hosts a high number of threatened plant species

Modelling the spatial distribution of EUNIS forest habitats based on vegetation relevés and Copernicus HRL : Using habitat suitability maps based on vegetation relevés and and amongst others the Copernicus high resolution layer forest, this report describes in detail the method used to produce the probability maps for the EUNIS forest habitat types at level 3. An assessment of these maps has been done for the whole of Slovakia. All the maps are presented in Annex I.

Using habitat suitability maps based on vegetation relevés and and amongst others the Copernicus high resolution layer forest, this report describes in detail the method used to produce the probability maps for the EUNIS forest habitat types at level 3. An assessment of these maps has been done for the whole of Slovakia. All the maps are presented in Annex I

Linking pan-European land cover change to pressures on biodiversity - Biopress final report 1st January 2003 - 31st December 2005, sections 5 and 6

BIOPRESS – Linking pan-European land cover change to pressures on biodiversity – is a 3 year EC-FPV project funded in the framework of the GMES ‘Global Monitoring for Environment and Security’ initiative (http://gmes.fdc.fr/what_is/home.html). It was the only GMES project under the priority theme "Land cover change in Europe”. BIOPRESS’s main goal was to provide the EU-user community with quantitative information on how changes in land cover and land use has affected the environment and biodiversity in Europe. The project aimed at producing consistent and coherent sets of historical (1950 – 1990 – 2000) land cover change information in and around circa 75 Natura2000 sites located from the boreal to the Mediterranean, and from the Atlantic to the continental regions of Europe. These land cover change statistics would be converted into quantitative measures of pressures on biodiversity through the integration of socio-economic indicators. The impact of the land cover changes on biodiversity would also be assessed. The change statistics were produced by means of two parallel activities, the backdating of CORINE land cover 1990 of circa 75 windows (30km x30km) with aerial photography of the 1950’ies and, the interpretation of aerial photography from 1950, 1990 and 2000 for circa 50 transects (2km x 15km). The windows were interpreted to identify the CORINE level 3 land cover and use classes to a minimum mapping unit of 25 ha. The transects, at the other hand, were interpreted to a minimum mapping unit of 0.5 ha. Scientific achievements: Data access The BIOPRESS team established an operational online access point for metadata and data of relevant European datasets. The European data policy appears to be the major obstacle for easy access to European datasets even in case of projects that are financed by the European Commission. The INSPIRE initiative as well as the GMES framework could benefit from the experiences made in the BIOPRESS project in order to streamline access to European wide data relevant for environmental monitoring. Land Cover change The methodological development for production of land cover change matrices was completed successfully ensuring the BIOPRESS team had the appropriate tools (list of 30km x 30km window sites, list of 2km x 15km transect sites, interpretation manual, quality assurance protocol and meta database designed to follow progress) and material (aerial photography) to successfully carry out the photo to photo (1950 – 1990 – 2000) interpretation of transects and CORINE Land Cover 1990 backdating (1950-1990). Several of the tools, in particular the interpretation manuals, have the potential of being adopted by GMES services and future EU projects (The GEOLAND and GSELAND projects were given copies of the manuals on request). A total of 57 transects and 73 windows were interpreted. The results were stored in a database. The database will be made available to the wider research community in 2007. The total extent of land cover changes that have occurred within all BIOPRESS windows account only to 9,62 % of the total measured area. In other words, 90,38% of the measured area within the BIOPRESS windows have shown no change of land cover at all. Overall the most important land cover conversions based on CORINE level 2 nomenclature can be summarised as one of the following: • FROM shrub and/or herbaceous vegetation association TO forests, and its inverse conversion, FROM forest TO shrub and/or herbaceous vegetation association • FROM heterogeneous agricultural areas TO urban fabric, as well as TO forest • FROM arable land TO industrial, commercial, and transport units. Because the focus was on biodiversity and historical land cover changes, it was clear from the start that Europe had to be sampled. Bias was introduced in the BIOPRESS samples by (1) relying on an expert to select a superset of samples including Natura 2000 sites and (2) the availability of aerial photography. The project’s resources limited the total number of samples acquired. As a result some bio-geographical regions were under represented in the sample (Boreal and Mediterranean) whilst other regions were over represented (the Alpine, Atlantic, and Continental). So the development of an appropriate extrapolation approach was seen as a challenge from the beginning of the project. The key was to produce information which is useable in the data integration and which is meaningful, and reliable enough for use by our key stakeholder, the EEA. An extensive sensitivity analysis and the development of minimum land cover accordance maps have provided an excellent insight in the acquired land cover change data with respect to samples’ representativeness of biogeographical areas and land cover. Quality assurance and error propagation The following problems were identified as the main sources of possible mistakes and lack of correspondence in windows: • Ambiguity of CLC classes delineation. • Quality of B&W AP. • Availability of ancillary data. • Separation of CLC classes in B&W AP (E.g. burnt areas). • Diversity within class definition. • Occurrence of polygon less than 0.5 ha. • Amalgamation of objects less than 0.5 ha. • Real changes omitted. • Identification of questionable changes. • Identification of point and linear features, questionable, ambiguity and unknown relevance The quality of the input data was comparable for all transects, indicating that the comparability of results between partners and transects was unlikely to have been influenced by the quality of the input data. The date of the aerial photos (1950, 1990 or 2000) proved to have no influence on the thematic consistency of the interpretations whereas the level of thematic detail did have a high impact. The geometric accuracy was more difficult to evaluated, still we found that the controllers identified more spatial structures than the local interpreters. The quality of the interpretation depends on the land cover characteristics of the individual transects or windows. An error model was developed describing each step of the land cover change production chain. We found that most error sources which reduced the interpretation quality such as image quality, unclear class definition and confusion caused by lax use of land cover and land use attributes in the definitions, can be almost completely reduced by using modern data sources and adjusting the interpretation methodology. However, knowledge and experience of the interpreter play an important role in manual visual interpretation of remotely sensed data. Land cover change and pressures A land cover change - pressure association matrix was developed. This matrix enabled the grouping of types of land cover changes related to one of the six pressures under consideration in BIOPRESS: Urbanisation, intensification, afforestation, deforestation, abandonment and drainage. This cross-tabulation matrix is a fundamental starting point in the analysis of land cover change, because it provides a national-scale assessment of not only the losses or gains in the area of specific land categories but what these changes represent in terms of types of pressures However, additional research is needed to analyse this matrix according to its various components in order to gain more insight into the potential processes that determine a pattern of land cover change. It was impossible to derive a simple and practical list of indicators that would consistently explain the pressures on biodiversity. It was clear that there were multiple potential indicators, and the best indicators have not simply appeared out from the extensive data and information that already existed. In essence, the search for a coherent set of pressure indicators was a frustrating and time-consuming activity. It is clear from our effort that a single set of indicators would never explain the whole dynamics of anthropogenic pressures on biodiversity, and would go only some way towards meeting the needs for understanding the observed land cover changes. The main research challenge faced was to define a pattern-process model of land cover dynamics in space and time in order to combine the local level measurement of the land cover changes (e.g. BIOPRESS windows) and the socio-economic indicators of a larger region (e.g. the countries). The proposed multi-representation model is based on the degree of variability in the behaviour of generalised statistics and their dependency of the spatial generalisation of the variable values at different spatial scales. A systematic analysis of spatial coincidence between land cover types in CLC1990 and Annex1 habitat types recorded in Natura 2000 sites was carried out, translated into the EUNIS habitat classification and summarised per Biogeographical region. The work showed that a significant improvement could be made by adopting a regional approach providing neater and more specific links between CLC classes and habitats than what has been available so far. It also identifies what the limitations are in attributing habitat types to CLC classes. We found that the BIOPRESS land cover change product was suitable for quantifying some pressures on biodiversity but quite insufficient for the interpretation of land cover change related to other pressures: • BIOPRESS contributed very positively to the quantification of urbanization across Europe between 1950 and 1990/2000. • BIOPRESS land cover product made a useful contribution to the quantification of afforestation and deforestation across Europe between 1950 and 1990 but that these pressures could be better understood if (i) we had more points in time, closer together and (ii) more information on the condition of forest was derived from remote sensing and/or ancillary data was used to evaluate the ecological value of forested land. • BIOPRESS will have underestimated the extent to which the pressure land abandonment is threatening biodiversity in Europe, in comparison to other existing assessments (e.g. MIRABEL but also national scale statements). However, it would be possible to increase the accuracy and the generic value of the BIOPRESS estimates by (i) broadening the definition of land abandonment i.e. modifying the pressure matrix, so that it matches what is meant in other assessments and (ii) by increasing the number of points in time. • BIOPRESS was probably the first project to provide quantitative estimates about the shift from small scale to more large scale agriculture for such a large sample area across Europe and in this respect, this is a very important contribution to understanding changes in European biodiversity. However it is important to keep in mind that what has been quantified within BIOPRESS was only a small part of what is usually understood by farming intensification in biodiversity assessments. This means that, as was the case for land abandonment, BIOPRESS results will greatly underestimate the pressure farming intensification, compared to other assessments. The main conclusion is that remote sensing products such as the BIOPRESS land cover change product can provide very helpful information in the field of biodiversity assessment. There is potential for improving this information, e.g. by adding time steps in the monitoring or using external data to help in the interpretation of land cover change. However, our work also shows that there are clear limitations in this contribution and that remote sensing will only provide part of the information. One important recommendation that would lead to improve facilities for large scale biodiversity monitoring would be the integration of remote sensing products with in situ information. This recommendation forms the basis of a position paper produced jointly by BIOHAB (FP5 funded Concerted Action) and BIOPRESS. Socio-economic relevance and policy implications: The project supported the needs of DG-Environment and EEA in helping to implement and assess European policy on nature and biodiversity and contribute to the objective of enhancing the quality of the environment by helping to understand pressures on biodiversity arising from land cover change in the member states and accession countries. The state of the environment is perceived as an important indicator of a high quality of life by a majority of European citizens. The European public increasingly expresses the wish to be informed by policy on the perceived threats to biodiversity. BIOPRESS supported the development of a European capacity for monitoring the state of the environment (GMES) to meet these information needs. Conclusions: BIOPRESS was one of the first wave of thematic projects which were funded through the GMES initiative. As a result its main objective was to produce information at European level which in the case of BIOPRESS was information on historical land cover change for the purpose of assessing past pressures on habitats and their associated biodiversity. A large part of the project’s resources were used to deliver the land cover change database successfully and the outcome has not only been the delivery of data but also a set of tools for future European wide land cover monitoring. The real challenge was when trying to establish a link between land cover change and pressures on biodiversity. The development of the land cover change - pressure association matrix as a first step enabled the grouping of types of land cover changes related to one of the six pressures under consideration in BIOPRESS. This matrix has the potential to enhance the similar ‘Land Cover Flow’ matrix developed by the EEA as part of the EEA Land Accounting System. In theory the idea of integrating socio-economic data with land cover change data made sense but in practice the team struggled with the wide variety of data types, spatial and temporal resolutions. To assess the consequences of the observed Land cover changes on habitats and their biodiversity, BIOPRESS impact tables were developed using the same conceptual approach as that establish for the DPSIR assessment MIRABEL. The overall agreement between MIRABEL and the BIOPRESS tables, which unlike MIRABLE provided quantitative estimates for a selected sample of land in each region, was an important result. This part of the work concluded that a land cover change product such as that produced by BIOPRESS was suitable for quantifying some pressures on biodiversity but quite insufficient for the interpretation of land cover change related to other pressures. The error propagation, quality assessment and data search exercises highlighted the importance of the availability of good quality, affordable data (e.g. aerial photography, digital elevation data, social and economic indicators) which for long term monitoring should be continuously collected in a consistent manner

Linking pan-European land cover change to pressures on biodiversity - Biopress final report 1st January 2003 - 31st December 2005, sections 1 to 4

BIOPRESS – Linking pan-European land cover change to pressures on biodiversity – is a 3 year EC-FPV project funded in the framework of the GMES ‘Global Monitoring for Environment and Security’ initiative (http://gmes.fdc.fr/what_is/home.html). It was the only GMES project under the priority theme "Land cover change in Europe”. BIOPRESS’s main goal was to provide the EU-user community with quantitative information on how changes in land cover and land use has affected the environment and biodiversity in Europe. The project aimed at producing consistent and coherent sets of historical (1950 – 1990 – 2000) land cover change information in and around circa 75 Natura2000 sites located from the boreal to the Mediterranean, and from the Atlantic to the continental regions of Europe. These land cover change statistics would be converted into quantitative measures of pressures on biodiversity through the integration of socio-economic indicators. The impact of the land cover changes on biodiversity would also be assessed. The change statistics were produced by means of two parallel activities, the backdating of CORINE land cover 1990 of circa 75 windows (30km x30km) with aerial photography of the 1950’ies and, the interpretation of aerial photography from 1950, 1990 and 2000 for circa 50 transects (2km x 15km). The windows were interpreted to identify the CORINE level 3 land cover and use classes to a minimum mapping unit of 25 ha. The transects, at the other hand, were interpreted to a minimum mapping unit of 0.5 ha. Scientific achievements: Data access The BIOPRESS team established an operational online access point for metadata and data of relevant European datasets. The European data policy appears to be the major obstacle for easy access to European datasets even in case of projects that are financed by the European Commission. The INSPIRE initiative as well as the GMES framework could benefit from the experiences made in the BIOPRESS project in order to streamline access to European wide data relevant for environmental monitoring. Land Cover change The methodological development for production of land cover change matrices was completed successfully ensuring the BIOPRESS team had the appropriate tools (list of 30km x 30km window sites, list of 2km x 15km transect sites, interpretation manual, quality assurance protocol and meta database designed to follow progress) and material (aerial photography) to successfully carry out the photo to photo (1950 – 1990 – 2000) interpretation of transects and CORINE Land Cover 1990 backdating (1950-1990). Several of the tools, in particular the interpretation manuals, have the potential of being adopted by GMES services and future EU projects (The GEOLAND and GSELAND projects were given copies of the manuals on request). A total of 57 transects and 73 windows were interpreted. The results were stored in a database. The database will be made available to the wider research community in 2007. The total extent of land cover changes that have occurred within all BIOPRESS windows account only to 9,62 % of the total measured area. In other words, 90,38% of the measured area within the BIOPRESS windows have shown no change of land cover at all. Overall the most important land cover conversions based on CORINE level 2 nomenclature can be summarised as one of the following: • FROM shrub and/or herbaceous vegetation association TO forests, and its inverse conversion, FROM forest TO shrub and/or herbaceous vegetation association • FROM heterogeneous agricultural areas TO urban fabric, as well as TO forest • FROM arable land TO industrial, commercial, and transport units. Because the focus was on biodiversity and historical land cover changes, it was clear from the start that Europe had to be sampled. Bias was introduced in the BIOPRESS samples by (1) relying on an expert to select a superset of samples including Natura 2000 sites and (2) the availability of aerial photography. The project’s resources limited the total number of samples acquired. As a result some bio-geographical regions were under represented in the sample (Boreal and Mediterranean) whilst other regions were over represented (the Alpine, Atlantic, and Continental). So the development of an appropriate extrapolation approach was seen as a challenge from the beginning of the project. The key was to produce information which is useable in the data integration and which is meaningful, and reliable enough for use by our key stakeholder, the EEA. An extensive sensitivity analysis and the development of minimum land cover accordance maps have provided an excellent insight in the acquired land cover change data with respect to samples’ representativeness of biogeographical areas and land cover. Quality assurance and error propagation The following problems were identified as the main sources of possible mistakes and lack of correspondence in windows: • Ambiguity of CLC classes delineation. • Quality of B&W AP. • Availability of ancillary data. • Separation of CLC classes in B&W AP (E.g. burnt areas). • Diversity within class definition. • Occurrence of polygon less than 0.5 ha. • Amalgamation of objects less than 0.5 ha. • Real changes omitted. • Identification of questionable changes. • Identification of point and linear features, questionable, ambiguity and unknown relevance The quality of the input data was comparable for all transects, indicating that the comparability of results between partners and transects was unlikely to have been influenced by the quality of the input data. The date of the aerial photos (1950, 1990 or 2000) proved to have no influence on the thematic consistency of the interpretations whereas the level of thematic detail did have a high impact. The geometric accuracy was more difficult to evaluated, still we found that the controllers identified more spatial structures than the local interpreters. The quality of the interpretation depends on the land cover characteristics of the individual transects or windows. An error model was developed describing each step of the land cover change production chain. We found that most error sources which reduced the interpretation quality such as image quality, unclear class definition and confusion caused by lax use of land cover and land use attributes in the definitions, can be almost completely reduced by using modern data sources and adjusting the interpretation methodology. However, knowledge and experience of the interpreter play an important role in manual visual interpretation of remotely sensed data. Land cover change and pressures A land cover change - pressure association matrix was developed. This matrix enabled the grouping of types of land cover changes related to one of the six pressures under consideration in BIOPRESS: Urbanisation, intensification, afforestation, deforestation, abandonment and drainage. This cross-tabulation matrix is a fundamental starting point in the analysis of land cover change, because it provides a national-scale assessment of not only the losses or gains in the area of specific land categories but what these changes represent in terms of types of pressures However, additional research is needed to analyse this matrix according to its various components in order to gain more insight into the potential processes that determine a pattern of land cover change. It was impossible to derive a simple and practical list of indicators that would consistently explain the pressures on biodiversity. It was clear that there were multiple potential indicators, and the best indicators have not simply appeared out from the extensive data and information that already existed. In essence, the search for a coherent set of pressure indicators was a frustrating and time-consuming activity. It is clear from our effort that a single set of indicators would never explain the whole dynamics of anthropogenic pressures on biodiversity, and would go only some way towards meeting the needs for understanding the observed land cover changes. The main research challenge faced was to define a pattern-process model of land cover dynamics in space and time in order to combine the local level measurement of the land cover changes (e.g. BIOPRESS windows) and the socio-economic indicators of a larger region (e.g. the countries). The proposed multi-representation model is based on the degree of variability in the behaviour of generalised statistics and their dependency of the spatial generalisation of the variable values at different spatial scales. A systematic analysis of spatial coincidence between land cover types in CLC1990 and Annex1 habitat types recorded in Natura 2000 sites was carried out, translated into the EUNIS habitat classification and summarised per Biogeographical region. The work showed that a significant improvement could be made by adopting a regional approach providing neater and more specific links between CLC classes and habitats than what has been available so far. It also identifies what the limitations are in attributing habitat types to CLC classes. We found that the BIOPRESS land cover change product was suitable for quantifying some pressures on biodiversity but quite insufficient for the interpretation of land cover change related to other pressures: • BIOPRESS contributed very positively to the quantification of urbanization across Europe between 1950 and 1990/2000. • BIOPRESS land cover product made a useful contribution to the quantification of afforestation and deforestation across Europe between 1950 and 1990 but that these pressures could be better understood if (i) we had more points in time, closer together and (ii) more information on the condition of forest was derived from remote sensing and/or ancillary data was used to evaluate the ecological value of forested land. • BIOPRESS will have underestimated the extent to which the pressure land abandonment is threatening biodiversity in Europe, in comparison to other existing assessments (e.g. MIRABEL but also national scale statements). However, it would be possible to increase the accuracy and the generic value of the BIOPRESS estimates by (i) broadening the definition of land abandonment i.e. modifying the pressure matrix, so that it matches what is meant in other assessments and (ii) by increasing the number of points in time. • BIOPRESS was probably the first project to provide quantitative estimates about the shift from small scale to more large scale agriculture for such a large sample area across Europe and in this respect, this is a very important contribution to understanding changes in European biodiversity. However it is important to keep in mind that what has been quantified within BIOPRESS was only a small part of what is usually understood by farming intensification in biodiversity assessments. This means that, as was the case for land abandonment, BIOPRESS results will greatly underestimate the pressure farming intensification, compared to other assessments. The main conclusion is that remote sensing products such as the BIOPRESS land cover change product can provide very helpful information in the field of biodiversity assessment. There is potential for improving this information, e.g. by adding time steps in the monitoring or using external data to help in the interpretation of land cover change. However, our work also shows that there are clear limitations in this contribution and that remote sensing will only provide part of the information. One important recommendation that would lead to improve facilities for large scale biodiversity monitoring would be the integration of remote sensing products with in situ information. This recommendation forms the basis of a position paper produced jointly by BIOHAB (FP5 funded Concerted Action) and BIOPRESS. Socio-economic relevance and policy implications: The project supported the needs of DG-Environment and EEA in helping to implement and assess European policy on nature and biodiversity and contribute to the objective of enhancing the quality of the environment by helping to understand pressures on biodiversity arising from land cover change in the member states and accession countries. The state of the environment is perceived as an important indicator of a high quality of life by a majority of European citizens. The European public increasingly expresses the wish to be informed by policy on the perceived threats to biodiversity. BIOPRESS supported the development of a European capacity for monitoring the state of the environment (GMES) to meet these information needs. Conclusions: BIOPRESS was one of the first wave of thematic projects which were funded through the GMES initiative. As a result its main objective was to produce information at European level which in the case of BIOPRESS was information on historical land cover change for the purpose of assessing past pressures on habitats and their associated biodiversity. A large part of the project’s resources were used to deliver the land cover change database successfully and the outcome has not only been the delivery of data but also a set of tools for future European wide land cover monitoring. The real challenge was when trying to establish a link between land cover change and pressures on biodiversity. The development of the land cover change - pressure association matrix as a first step enabled the grouping of types of land cover changes related to one of the six pressures under consideration in BIOPRESS. This matrix has the potential to enhance the similar ‘Land Cover Flow’ matrix developed by the EEA as part of the EEA Land Accounting System. In theory the idea of integrating socio-economic data with land cover change data made sense but in practice the team struggled with the wide variety of data types, spatial and temporal resolutions. To assess the consequences of the observed Land cover changes on habitats and their biodiversity, BIOPRESS impact tables were developed using the same conceptual approach as that establish for the DPSIR assessment MIRABEL. The overall agreement between MIRABEL and the BIOPRESS tables, which unlike MIRABLE provided quantitative estimates for a selected sample of land in each region, was an important result. This part of the work concluded that a land cover change product such as that produced by BIOPRESS was suitable for quantifying some pressures on biodiversity but quite insufficient for the interpretation of land cover change related to other pressures. The error propagation, quality assessment and data search exercises highlighted the importance of the availability of good quality, affordable data (e.g. aerial photography, digital elevation data, social and economic indicators) which for long term monitoring should be continuously collected in a consistent manner

Land cover change in Europe between 1950 and 2000 determined employing aerial photography

BIOPRESS (‘Linking Pan-European land cover change to pressures on Biodiversity’), a European Commission funded ‘Global Monitoring for Environment and Security’ project produced land cover change information (1950–2000) for Europe from aerial photographs and tested if this information is suitable for monitoring habitats and biodiversity. The methods and results related to the land cover change work are summarised. Changes in land cover were established through 73 window and 59 transect samples distributed across Europe. Although the sample size was too small and biased to represent the spatial variability observed in Europe, the work highlighted the importance of method consistency, the choice of nomenclature and spatial scale. The results suggest different processes are taking place in different parts of Europe: the Boreal and Alpine regions are dominated by forest management; abandonment and intensification are mainly encountered in the Mediterranean; urbanisation and drainage are more characteristic of the Continental and Atlantic regions